adding annotation to illumina data
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Kripa R ▴ 180
@kripa-r-4482
Last seen 10.2 years ago
Hello, I'm trying to analyze 11 samples from illumina HT12 chips. In the lumi package I set Although I set convert NuID and input annotation to be true, after using limma my top table does not show the gene symbol or name. Loading required package: annotate ID geneSymbol geneName logFC AveExpr t 4894 2230037 NA NA 11.93955 12.13396 100.74365 1211 610112 NA NA 11.55668 11.63635 99.67799 I was wondering how I'd be able to add this information and export it. Any help would be greatly appreciated! > sessionInfo() R version 2.12.2 (2011-02-25) Platform: i386-pc-mingw32/i386 (32-bit) locale: [1] LC_COLLATE=English_Canada.1252 LC_CTYPE=English_Canada.1252 [3] LC_MONETARY=English_Canada.1252 LC_NUMERIC=C [5] LC_TIME=English_Canada.1252 attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] annotate_1.28.0 lumiHumanAll.db_1.12.0 org.Hs.eg.db_2.4.6 [4] RSQLite_0.9-2 DBI_0.2-5 AnnotationDbi_1.12.0 [7] limma_3.6.9 lumi_2.2.1 Biobase_2.10.0 loaded via a namespace (and not attached): [1] affy_1.28.0 affyio_1.18.0 grid_2.12.0 [4] hdrcde_2.15 KernSmooth_2.23-4 lattice_0.19-13 [7] MASS_7.3-8 Matrix_0.999375-44 methylumi_1.6.1 [10] mgcv_1.6-2 nlme_3.1-97 preprocessCore_1.12.0 [13] tools_2.12.0 xtable_1.5-6 #------------------------------------------------------------# ###HT-12 illumina data. 11samples, 3 groups #group1:AJ #group2:BCDH #group3:EFGIKL #------------------------------------------------------------# ###PREAMBLE############################### library("lumi"); date <- Sys.Date(); #################################################### setwd("\\\\rinas1p2/users/ramank/Illumina/NugenAnalysis") #load raw data data<- "FinalReportA-K.txt"; #read data x.lumi<-lumiR(fileName=data, sep="\t", detectionTh=0.01, na.rm=TRUE, convertNuID=TRUE, lib.mapping=NULL, dec='.', parseColumnName=TRUE, checkDupId=TRUE, QC=TRUE, columnNameGrepPattern=list(exprs='AVG_Signal', se.exprs='BEAD_STDERR', detection='Detection Pval', beadNum='Avg_NBEADS'), inputAnnotation=TRUE, annotationColumn=c('ACCESSION', 'SYMBOL', 'PROBE_START', 'CHROMOSOME', 'PROBE_CHR_ORIENTATION', 'PROBE_COORDINATES', 'DEFINITION'), verbose=TRUE); #summary of the quality control summary(x.lumi, 'QC'); ##????how to write this to a txt file?????## #########2 PRE PROCESSING METHODS (LUMI)################## ############ ###no background correction since no control, #variance stabilization = log2 #normalization = quantile noBg_log_quantile <- lumiExpresso( x.lumi, bg.correct = TRUE, bgcorrect.param = list(method='none'), variance.stabilize = TRUE, varianceStabilize.param = list(method='log2'), normalize = TRUE, normalize.param = list(method='quantile'), QC.evaluation = TRUE, QC.param = list(), verbose = TRUE) summary(noBg_log_quantile,'QC') #making matrix of the data lumi.N.Q <- noBg_log_quantile dataMatrix <- exprs(lumi.N.Q); #filtering presentCount <- detectionCall(x.lumi); selDataMatrix <- dataMatrix[presentCount > 0,]; probeList <- rownames(selDataMatrix); #################################################################### ## LIMMA #################################################################### SampleType <- c('1','2','2','2','3','3','3','2','3','1','3') ##????above line correct?????## if (require(limma)) { ## compare '1' and '2' and '3' design <- model.matrix(~ factor(sampleType)) colnames(design) <- c('1', '2', '3') fit <- lmFit(selDataMatrix, design) fit <- eBayes(fit) ## Add gene symbols to gene properties if (require(lumiHumanAll.db) & require(annotate)) { geneSymbol <- getSYMBOL(probeList, 'lumiHumanAll.db') geneName <- sapply(lookUp(probeList, 'lumiHumanAll.db', 'GENENAME'), function(x) x[1]) fit$genes <- data.frame(ID= probeList, geneSymbol=geneSymbol, geneName=geneName, stringsAsFactors=FALSE) } ## print the top 10 genes print(topTable(fit, coef='1', adjust='fdr', number=10)) ## get significant gene list with FDR adjusted p.values less than 0.01 p.adj <- p.adjust(fit$p.value[,2]) sigGene.adj <- probeList[ p.adj < 0.01] ## without FDR adjustment sigGene <- probeList[ fit$p.value[,2] < 0.01] } ; .kripa [[alternative HTML version deleted]]
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